The present invention relates generally to image processing, and more particularly to methods, systems, and applications for detecting text in raster images.
Many images (taken by camera or created by an artist) contain text. Text can hold significant information, so the task of detecting and recognizing text (i.e., converting into characters for storing and processing by a computer system) is important. Typical processing steps are: image clean-up (remove noise and reduce the number of colors), detection of text block candidates (blocks of pixels which may represent some text), classification of the candidate blocks into text and non-text, translation of text-like blocks into sequences of text characters (text recognition).
One method for detecting text in images is known as Optical Character Recognition (or “OCR”). Modern commercial OCRs do a very good job of recognizing black-and-white or grayscale text consisting of rectangular text lines of sufficient length. Error rates are very low for even noisy and low-contrast images. However, OCR pre-preprocessing does not perform well on images containing text which is short, curved, or on a busy background. A need therefore exists for an improved method for pre-processing such image, detecting, classifying and straightening text candidate blocks.